A Logic of Trust and Reputation

Size: px
Start display at page:

Download "A Logic of Trust and Reputation"

Transcription

1 A Logic of Trust and Reputation Emiliano Lorini (joint work with A. Herzig, J. F. Hübner, L. Vercouter) IRIT-CNRS, Toulouse, France Workshop on Trust, Advice, and Reputation Toulouse, October 2009

2 Motivation: formal analysis of trust and reputation many computational models [Sabater & Sierra 02; Huynh et al. 04] quantitative no qualitative analysis few logical models mostly focused on trust in information sources [Liau 03; Jones & Firozabadi 01; Dastani et al. 04] cognitive model of trust [Castelfranchi & Falcone 98, 01] informal definitions formal definitions? relations between trust and reputation?

3 Contribution: definitions in a BDI logic [Lorini & Demolombe 2008, 2009; Lorini, Falcone, Castelfranchi 2008; Herzig, Lorini, Hübner, Vercouter 2009] top-down qualitative analysis: reduction of trust to more primitive concepts trust belief, goal, intention, action analysis in terms of logics of action and time, BDI logics two versions of trust occurrent trust vs. dispositional trust refinement of Castelfranchi & Falcone s definition from dispositional trust to reputation

4 Trust: the ingredients [Castelfranchi & Falcone] i trusts j to do α in order to achieve ϕ truster i, trustee j, action α of j, goal ϕ of i. important: trust thinking and foreseeing

5 Informal definition [Castelfranchi & Falcone] trust evaluation of the truster about certain properties of trustee (that are relevant for a goal/task ϕ) i trusts j to do α in order to achieve ϕ if and only if: 1 i has the goal ϕ; 2 i believes that 1 j is capable to do α; 2 j has the power to achieve ϕ by doing α; 3 j intends to do α. trust defined from four more primitive concepts logic of goal, ability, power and intention?

6 1 Two kinds of trust: occurrent vs. dispositional 2 Logical formalization 3 From trust to reputation 4 Conclusion

7 Two kinds of trust: occurrent vs. dispositional

8 Occurrent trust vs. dispositional trust two perspectives on trustee s action α: truster believes trustee is going to do α here and now occurrent trust truster believes trustee is going to do α whenever some conditions are satisfied. dispositional trust (cf. occurrent belief vs. dispositional belief [Searle 92])

9 Occurrent trust i wants ϕ to be true and believes j is going to perform α here and now so that ϕ will be ensured OccTrust(i, j, α, ϕ) def = OccGoal(i, ϕ) Belief (i, OccCap(j, α) OccPower(j, α, ϕ) OccIntends(j, α)) predicates to be defined: Belief, OccGoal, OccCap, OccPower, OccIntends

10 Example 1 s occurrent trust in 2 to send a certain product in view of satisfying 1 s goal of possessing the product: 1 wants to possess the product, 1 believes that 2 is capable to send the product, 2 s act of sending the product will result in 1 possessing it, 2 has the intention to send the product.

11 Dispositional trust i expects that there will be some situations κ in which he will have the goal of achieving ϕ (potential goal), and believes that in all these situations j will ensure ϕ by doing action α DispTrust(i, j, α, ϕ, κ) def = PotGoal(i, ϕ, κ) Belief (i, Henceforth ((κ OccGoal(i, ϕ)) (OccCap(j, α) OccPower(j, α, ϕ) OccIntends(j, α))) predicates to be defined: PotGoal, Belief, Henceforth, OccGoal, OccCap, OccPower, OccIntends

12 Example 1 s dispositional trust in 2 (a mechanic) to repair his car so that the car will be in order, in the circumstances in which 1 will ask the mechanic to repair his car

13 Logical formalization

14 Occurrent trust and dispositional trust: components definiendum: belief, occurrent goal, occurrent capability, occurrent power, occurrent intention. definiens: formulas of a modal logic of time, belief, preference, and action spell out predicates Belief (i, ϕ), OccGoal(i, ϕ), PotGoal(i, ϕ, κ), OccCap(j, α), OccPower(j, α, ϕ), OccIntends(j, α) using modal operators of time, belief, preference, and action convention: Bel i, etc. = logical operators

15 Temporal operators Henceforth ϕ = ϕ henceforth holds Eventually ϕ def = Henceforth ϕ Eventually ϕ = ϕ eventually holds will be used to define OccGoal(i, ϕ), etc.

16 Belief operators Bel i ϕ = agent i believes that ϕ Poss i ϕ def = Bel i ϕ Poss i ϕ = agent i thinks that ϕ is possible epistemic and doxastic logic [Hintikka 62] express truster s beliefs about trustee s properties Belief (i, ϕ) def = Bel i ϕ

17 Goals as preferences about the future Pref i ϕ = agent i wants ϕ to be true binary preferences [Cohen & Levesque 90] positive introspection: Pref i ϕ Bel i Pref i ϕ negative introspection: Pref i ϕ Bel i Pref i ϕ realism: Bel i ϕ Pref i ϕ OccGoal(i, ϕ) def = Pref i Eventually ϕ

18 Capability in dynamic logic After i:α ϕ = ϕ will be true after every possible execution of action α by agent i propositional dynamic logic (PDL) formulas = ϕ, ψ,... = state descriptions actions = α, β,... = state transition descriptions action formula i : α = action α with author i After i:α = i cannot do α OccCap(j, α) def = After j:α j is capable to perform α = j can do α

19 Power in dynamic logic OccPower(j, α, ϕ) def = After j:α ϕ relates j s action α with i s goal ϕ missing: epistemic aspect of power ( knowing how to play )

20 Intention-to-do as preferred action Does i:α ϕ = agent i is going to do α and ϕ will be true afterwards Does i:α = i does α OccIntends(j, α) def = Pref j Does j:α Some axioms: Theorem 1 Does i:α ϕ After i:α ϕ ( Does i:α After i:α ) 2 (Pref i Does i:α After i:α ) Does i:α 3 Does i:α Pref i Does i:α (Pref i Does i:α After i:α ) Does i:α

21 Formal definition of occurrent trust OccTrust(i, j, α, ϕ) def = Pref i Eventually ϕ Bel i ( After j:α After j:α ϕ Pref j Does j:α )

22 Example 1 s occurrent trust in 2 to send a certain product in view of satisfying 1 s goal of possessing the product OccTrust(1, 2, sendp1, hasp1) def = Pref 1 Eventually hasp1 Bel 1 ( After 2:sendP1 After 2:sendP1 hasp1 Pref 2 Does 2:sendP1 )

23 Some properties of occurrent trust Theorem OccTrust(i, j, α, ϕ) (Pref i Eventually ϕ Bel i (Does i:α After j:α ϕ)) OccTrust(i, j, α, ϕ) Bel i OccTrust(i, j, α, ϕ) OccTrust(i, j, α, ϕ) Bel i Eventually ϕ

24 Potential goal PotGoal(i, ϕ, κ) def = Poss i Eventually (κ Pref i Eventually ϕ)

25 Formal definition of dispositional trust DispTrust(i, j, α, ϕ, κ) def = Poss i Eventually (κ Pref i Eventually ϕ) Bel i Henceforth ((κ Pref i Eventually ϕ) ( After j:α After j:α ϕ Pref j Does j:α ))

26 Example 1 s dispositional trust in 2 (a mechanic) to repair his car so that the car will be in order, in the circumstances in which 1 will ask the mechanic to repair his car DispTrust(1, 2, rep1c, OK1c, ask12) def = Poss 1 Eventually (ask12 Pref 1 Eventually OK1c) Bel 1 Henceforth ((ask12 Pref 1 Eventually OK1c) ( After 2:rep1c After 2:rep1c OK1c Pref 2 Does 2:rep1c ))

27 Some properties of dispositional trust Theorem DispTrust(i, j, α, ϕ, κ) (Poss i Eventually (κ Pref i Eventually ϕ) Bel i Henceforth ((κ Pref i Eventually ϕ) (Does i:α After j:α ϕ))) DispTrust(i, j, α, ϕ, κ) Bel i DispTrust(i, j, α, ϕ, κ)

28 From dispositional to occurrent trust Theorem (DispTrust(i, j, α, ϕ, κ) Pref i Eventually ϕ Bel i κ) OccTrust(i, j, α, ϕ)

29 Discussion: other definition of trust Deutsch s definition (1958): trust involves risk perception (trusting is doing a real bet on the trustee) Uncertain beliefs are needed to capture it Genuine trust (Trust game, Baier 1986, Holton 1994): i s belief that j has goodwill towards him (j is willing to sacrifice his wellbeing for i) It is just a special case of our definition Jones s definition (2002): rule belief+conformity belief Trust thinking or foreseeing

30 From trust to reputation

31 Reputation: the building blocks Rep(I, j, α, ϕ, κ) = j has reputation in group I to ensure ϕ by doing α in the circumstances κ Reputation as the collective counterpart of trust TRUST = agent i s individual evaluation (belief) about some properties of agent j that are relevant for a goal of i REPUTATION = group I s collective evaluation about some properties of agent j that are relevant for a (group) goal of I to be defined: collective evaluation, group goals

32 Public facts For every I such that I > 2, Public I ϕ = ϕ is public in the group of agents I ( ϕ is said in I ) ϕ is public in I common belief in I that ϕ ϕ is public in I does not imply every agent in I believes ϕ

33 Logic of public facts: some principles 1 (Public I ϕ Public I ϕ) 2 Public I ϕ Public J Public I ϕ if J I 3 Public I ϕ Public J Public I ϕ if J I 4 Public I ϕ Bel i Public I ϕ if i I 5 Public I ϕ Bel i Public I ϕ if i I 6 Public I ( i I Bel i ϕ ϕ)

34 Group goals GroupPref I ϕ = the agents in I want that ϕ group goals: broad sense (individual preference aggregation) weaker than joint goals and joint intentions [Grosz & Kraus 96] Some examples of GroupPref I ϕ definition: -group goal: i I Pref i ϕ -group goal: i I Pref i ϕ Group goal based on majority: J I, J > I\J i J Pref i ϕ

35 Formal definition of reputation Rep(I, j, α, ϕ, κ) def = PotGoal(I, ϕ) Poss I Henceforth ((κ GroupPref I Eventually ϕ) ( After j:α After j:α ϕ Pref j Does j:α )) Poss I ϕ def = Public I ϕ Poss I ϕ = according to the group I, ϕ is possible PotGoal(I, ϕ) def = Poss I Eventually (κ GroupPref I Eventually ϕ)

36 Conclusion

37 Conclusion Contribution. formal definitions of occurrent trust and dispositional trust formal definition of reputation and its relation with trust Our related works semantics for the different modalities mathematical properties of the logic of belief, preference, action and time (soundness, completeness) trust in information sources and in communication systems from binary trust to graded trust trust in agents vs. trust in roles Implementation of a BDI agent reasoning about trust (see Vercouter s presentation)

38 THANK YOU!

Comparing Formal Cognitive Emotion Theories

Comparing Formal Cognitive Emotion Theories Comparing Formal Cognitive Emotion Theories Koen V. Hindriks 1 and Joost Broekens 1 Delft University of Technology, The Netherlands, {k.v.hindriks,d.j.broekens}@tudelft.nl, WWW home page: http://mmi.tudelft.nl/~koen

More information

Trust Based Evaluation of Wikipedia s Contributors

Trust Based Evaluation of Wikipedia s Contributors Trust Based Evaluation of Wikipedia s Contributors Yann Krupa 1, Laurent Vercouter 1, Jomi F. Hübner 1,3, and Andreas Herzig 2 1 École Nationale Supérieure des Mines de Saint Etienne Centre G2I, Département

More information

Software Modeling and Verification

Software Modeling and Verification Software Modeling and Verification Alessandro Aldini DiSBeF - Sezione STI University of Urbino Carlo Bo Italy 3-4 February 2015 Algorithmic verification Correctness problem Is the software/hardware system

More information

Iterated Dynamic Belief Revision. Sonja Smets, University of Groningen. website: http://www.vub.ac.be/clwf/ss

Iterated Dynamic Belief Revision. Sonja Smets, University of Groningen. website: http://www.vub.ac.be/clwf/ss LSE-Groningen Workshop I 1 Iterated Dynamic Belief Revision Sonja Smets, University of Groningen website: http://www.vub.ac.be/clwf/ss Joint work with Alexandru Baltag, COMLAB, Oxford University LSE-Groningen

More information

A Model of Intention with (Un)Conditional Commitments

A Model of Intention with (Un)Conditional Commitments A Model of Intention with (Un)Conditional Commitments Dongmo Zhang Intelligent Systems Laboratory, University of Western Sydney, Australia d.zhang@uws.edu.au Abstract. This paper proposes a model of intention

More information

Formal Verification and Linear-time Model Checking

Formal Verification and Linear-time Model Checking Formal Verification and Linear-time Model Checking Paul Jackson University of Edinburgh Automated Reasoning 21st and 24th October 2013 Why Automated Reasoning? Intellectually stimulating and challenging

More information

Betting interpretations of probability

Betting interpretations of probability Betting interpretations of probability Glenn Shafer June 21, 2010 Third Workshop on Game-Theoretic Probability and Related Topics Royal Holloway, University of London 1 Outline 1. Probability began with

More information

Full and Complete Binary Trees

Full and Complete Binary Trees Full and Complete Binary Trees Binary Tree Theorems 1 Here are two important types of binary trees. Note that the definitions, while similar, are logically independent. Definition: a binary tree T is full

More information

AGENTS AND SOFTWARE ENGINEERING

AGENTS AND SOFTWARE ENGINEERING AGENTS AND SOFTWARE ENGINEERING Michael Wooldridge Queen Mary and Westfield College, University of London London E1 4NS, United Kingdom M.J.Wooldridge@qmw.ac.uk Abstract Software engineers continually

More information

Multi-agent belief dynamics: bridges between dynamic doxastic and doxastic temporal logics

Multi-agent belief dynamics: bridges between dynamic doxastic and doxastic temporal logics Multi-agent belief dynamics: bridges between dynamic doxastic and doxastic temporal logics Johan van Benthem ILLC Amsterdam Stanford University johan@science.uva.nl Cédric Dégremont ILLC Amsterdam cdegremo@science.uva.nl

More information

CSE 459/598: Logic for Computer Scientists (Spring 2012)

CSE 459/598: Logic for Computer Scientists (Spring 2012) CSE 459/598: Logic for Computer Scientists (Spring 2012) Time and Place: T Th 10:30-11:45 a.m., M1-09 Instructor: Joohyung Lee (joolee@asu.edu) Instructor s Office Hours: T Th 4:30-5:30 p.m. and by appointment

More information

Modeling Mental States in Requirements Engineering An Agent-Oriented Framework Based on i* and CASL

Modeling Mental States in Requirements Engineering An Agent-Oriented Framework Based on i* and CASL Modeling Mental States in Requirements Engineering An Agent-Oriented Framework Based on i* and CASL Alexei Lapouchnian A thesis submitted to the Faculty of Graduate Studies in partial fulfillment of the

More information

ON FUNCTIONAL SYMBOL-FREE LOGIC PROGRAMS

ON FUNCTIONAL SYMBOL-FREE LOGIC PROGRAMS PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY Physical and Mathematical Sciences 2012 1 p. 43 48 ON FUNCTIONAL SYMBOL-FREE LOGIC PROGRAMS I nf or m at i cs L. A. HAYKAZYAN * Chair of Programming and Information

More information

CSC 742 Database Management Systems

CSC 742 Database Management Systems CSC 742 Database Management Systems Topic #4: Data Modeling Spring 2002 CSC 742: DBMS by Dr. Peng Ning 1 Phases of Database Design Requirement Collection/Analysis Functional Requirements Functional Analysis

More information

A Propositional Dynamic Logic for CCS Programs

A Propositional Dynamic Logic for CCS Programs A Propositional Dynamic Logic for CCS Programs Mario R. F. Benevides and L. Menasché Schechter {mario,luis}@cos.ufrj.br Abstract This work presents a Propositional Dynamic Logic in which the programs are

More information

Which Semantics for Neighbourhood Semantics?

Which Semantics for Neighbourhood Semantics? Which Semantics for Neighbourhood Semantics? Carlos Areces INRIA Nancy, Grand Est, France Diego Figueira INRIA, LSV, ENS Cachan, France Abstract In this article we discuss two alternative proposals for

More information

CHAPTER 7 GENERAL PROOF SYSTEMS

CHAPTER 7 GENERAL PROOF SYSTEMS CHAPTER 7 GENERAL PROOF SYSTEMS 1 Introduction Proof systems are built to prove statements. They can be thought as an inference machine with special statements, called provable statements, or sometimes

More information

A Logic Approach for LTL System Modification

A Logic Approach for LTL System Modification A Logic Approach for LTL System Modification Yulin Ding and Yan Zhang School of Computing & Information Technology University of Western Sydney Kingswood, N.S.W. 1797, Australia email: {yding,yan}@cit.uws.edu.au

More information

A Geometry of Oriented Curves *

A Geometry of Oriented Curves * ftp://ftp.informatik.uni-hamburg.de/pub/unihh/informatik/wsv/trorientedcurves.pdf A Geometry of Oriented Curves * Lars Kulik & Carola Eschenbach Report from the project 'Axiomatics of Spatial Concepts'

More information

AGENT BASED SYSTEMS: THEORETICAL AND PRACTICAL GUIDE. Ali Orhan AYDIN *

AGENT BASED SYSTEMS: THEORETICAL AND PRACTICAL GUIDE. Ali Orhan AYDIN * 95 AGENT BASED SYSTEMS: THEORETICAL AND PRACTICAL GUIDE Ali Orhan AYDIN * ABSTRACT Purpose of this paper is to review the literature of Agent Based Systems. This research area became popular since 1980

More information

Software Verification and Testing. Lecture Notes: Temporal Logics

Software Verification and Testing. Lecture Notes: Temporal Logics Software Verification and Testing Lecture Notes: Temporal Logics Motivation traditional programs (whether terminating or non-terminating) can be modelled as relations are analysed wrt their input/output

More information

Chapter II. Controlling Cars on a Bridge

Chapter II. Controlling Cars on a Bridge Chapter II. Controlling Cars on a Bridge 1 Introduction The intent of this chapter is to introduce a complete example of a small system development. During this development, you will be made aware of the

More information

Obligations in a BDI Agent Architecture

Obligations in a BDI Agent Architecture Obligations in a BDI Agent Architecture Gordon Beavers and Henry Hexmoor University of Arkansas Computer Science & Computer Engineering Department Engineering Hall 313, Fayetteville AR 72701 {gordonb,

More information

Presentation Overview AGENT-BASED SOFTWARE ENGINEERING. 1 The AOP Proposal. 1.1 Specifics

Presentation Overview AGENT-BASED SOFTWARE ENGINEERING. 1 The AOP Proposal. 1.1 Specifics AGENT-BASED SOFTWARE ENGINEERING Mike Wooldridge & Michael Fisher Department of Computing Manchester Metropolitan University United Kingdom M.Wooldridge@doc.mmu.ac.uk Presentation Overview 1. Introduce

More information

Fixed-Point Logics and Computation

Fixed-Point Logics and Computation 1 Fixed-Point Logics and Computation Symposium on the Unusual Effectiveness of Logic in Computer Science University of Cambridge 2 Mathematical Logic Mathematical logic seeks to formalise the process of

More information

Development of dynamically evolving and self-adaptive software. 1. Background

Development of dynamically evolving and self-adaptive software. 1. Background Development of dynamically evolving and self-adaptive software 1. Background LASER 2013 Isola d Elba, September 2013 Carlo Ghezzi Politecnico di Milano Deep-SE Group @ DEIB 1 Requirements Functional requirements

More information

The epistemic structure of de Finetti s betting problem

The epistemic structure of de Finetti s betting problem The epistemic structure of de Finetti s betting problem Tommaso Flaminio 1 and Hykel Hosni 2 1 IIIA - CSIC Campus de la Univ. Autònoma de Barcelona s/n 08193 Bellaterra, Spain. Email: tommaso@iiia.csic.es

More information

Formal Specifications of Security Policy Models

Formal Specifications of Security Policy Models Wolfgang Thumser T-Systems GEI GmbH Overview and Motivation Structure of talk Position of FSPM within CC 3.1 and CEM 3.1 CC Requirements CEM Requirements National Scheme Realization of FSPM in terms of

More information

UNIVERSITY OF AMSTERDAM FACULTY OF SCIENCE. EDUCATION AND EXAMINATION REGULATIONS Academic Year 2012-2013 PART B THE MASTER S PROGRAMME IN LOGIC

UNIVERSITY OF AMSTERDAM FACULTY OF SCIENCE. EDUCATION AND EXAMINATION REGULATIONS Academic Year 2012-2013 PART B THE MASTER S PROGRAMME IN LOGIC UNIVERSITY OF AMSTERDAM FACULTY OF SCIENCE EDUCATION AND EXAMINATION REGULATIONS Academic Year 2012-2013 PART B THE MASTER S PROGRAMME IN LOGIC September 1 st 2012 Chapter 1 Article 1.1 Article 1.2 Chapter

More information

Algorithmic Software Verification

Algorithmic Software Verification Algorithmic Software Verification (LTL Model Checking) Azadeh Farzan What is Verification Anyway? Proving (in a formal way) that program satisfies a specification written in a logical language. Formal

More information

The result of the bayesian analysis is the probability distribution of every possible hypothesis H, given one real data set D. This prestatistical approach to our problem was the standard approach of Laplace

More information

INDUCTIVE & DEDUCTIVE RESEARCH APPROACH

INDUCTIVE & DEDUCTIVE RESEARCH APPROACH INDUCTIVE & DEDUCTIVE RESEARCH APPROACH Meritorious Prof. Dr. S. M. Aqil Burney Director UBIT Chairman Department of Computer Science University of Karachi burney@computer.org www.drburney.net Designed

More information

The Five Rules for Reliable Marketing Research

The Five Rules for Reliable Marketing Research URBAN WALLACE ASSOCIATES 35 Bedford St., Suite 8, Lexington, MA 02420 ph 781 862 0033 fax 781 862 1292 web www.uwa.com The Five Rules for Reliable Marketing Research Marketing Research Produces New Knowledge

More information

Lecture 13 of 41. More Propositional and Predicate Logic

Lecture 13 of 41. More Propositional and Predicate Logic Lecture 13 of 41 More Propositional and Predicate Logic Monday, 20 September 2004 William H. Hsu, KSU http://www.kddresearch.org http://www.cis.ksu.edu/~bhsu Reading: Sections 8.1-8.3, Russell and Norvig

More information

Appendices master s degree programme Artificial Intelligence 2014-2015

Appendices master s degree programme Artificial Intelligence 2014-2015 Appendices master s degree programme Artificial Intelligence 2014-2015 Appendix I Teaching outcomes of the degree programme (art. 1.3) 1. The master demonstrates knowledge, understanding and the ability

More information

Review. Bayesianism and Reliability. Today s Class

Review. Bayesianism and Reliability. Today s Class Review Bayesianism and Reliability Models and Simulations in Philosophy April 14th, 2014 Last Class: Difference between individual and social epistemology Why simulations are particularly useful for social

More information

Merging DEL and ETL. Noname manuscript No. (will be inserted by the editor) Tomohiro Hoshi

Merging DEL and ETL. Noname manuscript No. (will be inserted by the editor) Tomohiro Hoshi Noname manuscript No. (will be inserted by the editor) Merging DEL and ETL Tomohiro Hoshi Received: date / Accepted: date Abstract This paper surveys the interface between the two major logical trends

More information

Plenty of Blame to Go Around: A Qualitative Approach to Attribution of Moral Responsibility

Plenty of Blame to Go Around: A Qualitative Approach to Attribution of Moral Responsibility Plenty of Blame to Go Around: A Qualitative Approach to Attribution of Moral Responsibility Emmett Tomai Ken Forbus Qualitative Reasoning Group Northwestern University 2133 Sheridan Rd, Evanston, IL 60208

More information

MANY systems that are commonplace in our lives,

MANY systems that are commonplace in our lives, IEEE ACCESS 1 A Survey of Multi-agent Trust Management Systems Han Yu 1, Zhiqi Shen 1, Cyril Leung 2, Chunyan Miao 1, and Victor R. Lesser 3 1 School of Computer Engineering, Nanyang Technological University,

More information

Summary Last Lecture. Automated Reasoning. Outline of the Lecture. Definition sequent calculus. Theorem (Normalisation and Strong Normalisation)

Summary Last Lecture. Automated Reasoning. Outline of the Lecture. Definition sequent calculus. Theorem (Normalisation and Strong Normalisation) Summary Summary Last Lecture sequent calculus Automated Reasoning Georg Moser Institute of Computer Science @ UIBK Winter 013 (Normalisation and Strong Normalisation) let Π be a proof in minimal logic

More information

The Modal Logic Programming System MProlog

The Modal Logic Programming System MProlog The Modal Logic Programming System MProlog Linh Anh Nguyen Institute of Informatics, University of Warsaw ul. Banacha 2, 02-097 Warsaw, Poland nguyen@mimuw.edu.pl Abstract. We present the design of our

More information

Schedule. Logic (master program) Literature & Online Material. gic. Time and Place. Literature. Exercises & Exam. Online Material

Schedule. Logic (master program) Literature & Online Material. gic. Time and Place. Literature. Exercises & Exam. Online Material OLC mputational gic Schedule Time and Place Thursday, 8:15 9:45, HS E Logic (master program) Georg Moser Institute of Computer Science @ UIBK week 1 October 2 week 8 November 20 week 2 October 9 week 9

More information

Predicate logic Proofs Artificial intelligence. Predicate logic. SET07106 Mathematics for Software Engineering

Predicate logic Proofs Artificial intelligence. Predicate logic. SET07106 Mathematics for Software Engineering Predicate logic SET07106 Mathematics for Software Engineering School of Computing Edinburgh Napier University Module Leader: Uta Priss 2010 Copyright Edinburgh Napier University Predicate logic Slide 1/24

More information

How To Write Intuitionistic Logic

How To Write Intuitionistic Logic AN INTUITIONISTIC EPISTEMIC LOGIC FOR ASYNCHRONOUS COMMUNICATION by Yoichi Hirai A Master Thesis Submitted to the Graduate School of the University of Tokyo on February 10, 2010 in Partial Fulfillment

More information

An Operational Semantics for Knowledge Bases

An Operational Semantics for Knowledge Bases Appeared in: Proc. National Conference on Artificial Intelligence (AAAI-94), 1994, pp. 1142-1 147. An Operational Semantics for Knowledge Bases Ronald Fagin IBM Almaden Research Center 650 Harry Road San

More information

Trust in software agent societies

Trust in software agent societies Trust in software agent societies Mariusz Zytniewski, University of Economic, in Katowice, mariusz.zytniewski@ue.katowice.pl Mateusz Klement, University of Economics in Katowice, mateusz.klement@ue.katowice.pl

More information

def: An axiom is a statement that is assumed to be true, or in the case of a mathematical system, is used to specify the system.

def: An axiom is a statement that is assumed to be true, or in the case of a mathematical system, is used to specify the system. Section 1.5 Methods of Proof 1.5.1 1.5 METHODS OF PROOF Some forms of argument ( valid ) never lead from correct statements to an incorrect. Some other forms of argument ( fallacies ) can lead from true

More information

Review. Notre Dame Philosophical Reviews, 2008

Review. Notre Dame Philosophical Reviews, 2008 Notre Dame Philosophical Reviews, 2008 Review Jaakko Hintikka: Socratic Epistemology: Explorations of Knowledge-Seeking by Questioning. Cambridge University Press; 1 edition (September 3, 2007), 248 pp.,

More information

Model Checking: An Introduction

Model Checking: An Introduction Announcements Model Checking: An Introduction Meeting 2 Office hours M 1:30pm-2:30pm W 5:30pm-6:30pm (after class) and by appointment ECOT 621 Moodle problems? Fundamentals of Programming Languages CSCI

More information

MAT-71506 Program Verication: Exercises

MAT-71506 Program Verication: Exercises MAT-71506 Program Verication: Exercises Antero Kangas Tampere University of Technology Department of Mathematics September 11, 2014 Accomplishment Exercises are obligatory and probably the grades will

More information

Chapter 1 Verificationism Then and Now

Chapter 1 Verificationism Then and Now Chapter 1 Verificationism Then and Now Per Martin-Löf The term veri fi cationism is used in two different ways: the fi rst is in relation to the veri fi cation principle of meaning, which we usually and

More information

Vagueness, Uncertainty and Degrees of Clarity

Vagueness, Uncertainty and Degrees of Clarity Vagueness, Uncertainty and Degrees of Clarity Paul Égré Denis Bonnay Abstract The focus of the paper is on the logic of clarity and the problem of higherorder vagueness. We first examine the consequences

More information

SOFTWARE AGENTS AS LEGAL PERSONS

SOFTWARE AGENTS AS LEGAL PERSONS 01 SOFTWARE AGENTS AS LEGAL PERSONS Francisco Andrade 1, José Neves 2, Paulo Novais 2 and José Machado 2 1 Escola de Direito, Universidade do Minho, Braga, Portugal 2 Departamento de Informática, Universidade

More information

Jean Chen, Assistant Director, Office of Institutional Research University of North Dakota, Grand Forks, ND 58202-7106

Jean Chen, Assistant Director, Office of Institutional Research University of North Dakota, Grand Forks, ND 58202-7106 Educational Technology in Introductory College Physics Teaching and Learning: The Importance of Students Perception and Performance Jean Chen, Assistant Director, Office of Institutional Research University

More information

Position Paper for Cognition and Collaboration Workshop: Analyzing Distributed Community Practices for Design

Position Paper for Cognition and Collaboration Workshop: Analyzing Distributed Community Practices for Design Position Paper for Cognition and Collaboration Workshop: Analyzing Distributed Community Practices for Design Jean Scholtz, Michelle Steves, and Emile Morse National Institute of Standards and Technology

More information

Qualitative Analysis Vs. Quantitative Analysis 06/16/2014 1

Qualitative Analysis Vs. Quantitative Analysis 06/16/2014 1 Qualitative Analysis Vs. Quantitative Analysis 06/16/2014 1 What s the Difference? Qualitative adjustments are purely relative (inferior, similar and superior). Quantitative adjustments use specific numbers

More information

The History of Logic. Aristotle (384 322 BC) invented logic.

The History of Logic. Aristotle (384 322 BC) invented logic. The History of Logic Aristotle (384 322 BC) invented logic. Predecessors: Fred Flintstone, geometry, sophists, pre-socratic philosophers, Socrates & Plato. Syllogistic logic, laws of non-contradiction

More information

COMPUTER SCIENCE TRIPOS

COMPUTER SCIENCE TRIPOS CST.98.5.1 COMPUTER SCIENCE TRIPOS Part IB Wednesday 3 June 1998 1.30 to 4.30 Paper 5 Answer five questions. No more than two questions from any one section are to be answered. Submit the answers in five

More information

Developing Critical Thinking Skill in Mathematics Education

Developing Critical Thinking Skill in Mathematics Education Developing Critical Thinking Skill in Mathematics Education Einav Aizikovitsh-Udi In light of the importance of developing critical thinking, and given the scarcity of research on critical thinking in

More information

Verifying Multi-Agent Programs by Model Checking

Verifying Multi-Agent Programs by Model Checking Verifying Multi-Agent Programs by Model Checking Rafael H. Bordini 1, Michael Fisher 2, Willem Visser 3, and Michael Wooldridge 4 1 University of Durham, U.K. R.Bordini@durham.ac.uk 2 University of Liverpool,

More information

Foundational Proof Certificates

Foundational Proof Certificates An application of proof theory to computer science INRIA-Saclay & LIX, École Polytechnique CUSO Winter School, Proof and Computation 30 January 2013 Can we standardize, communicate, and trust formal proofs?

More information

Combining Sequential and Concurrent Verification - The SMTP Case Study -

Combining Sequential and Concurrent Verification - The SMTP Case Study - Deutsches Forschungszentrum für f r Künstliche K Intelligenz Combining Sequential and Concurrent Verification - The SMTP Case Study - Bruno Langenstein, Werner Stephan (DFKI GmbH) Saarbrücken, Germany

More information

The epistemic structure of de Finetti s betting problem

The epistemic structure of de Finetti s betting problem The epistemic structure of de Finetti s betting problem Tommaso Flaminio 1 Hykel Hosni 2 1 IIIA - CSIC Universitat Autonoma de Barcelona (Spain) tommaso@iiia.csic.es www.iiia.csic.es/ tommaso 2 SNS Scuola

More information

Introducing Formal Methods. Software Engineering and Formal Methods

Introducing Formal Methods. Software Engineering and Formal Methods Introducing Formal Methods Formal Methods for Software Specification and Analysis: An Overview 1 Software Engineering and Formal Methods Every Software engineering methodology is based on a recommended

More information

Software Verification and System Assurance

Software Verification and System Assurance Software Verification and System Assurance John Rushby Based on joint work with Bev Littlewood (City University UK) Computer Science Laboratory SRI International Menlo Park CA USA John Rushby, SR I Verification

More information

Indiana STANDARDS FOR TECHNOLOGICAL LITERACY. Mike Fitzgerald Technology Education Specialist Indiana Department of Education

Indiana STANDARDS FOR TECHNOLOGICAL LITERACY. Mike Fitzgerald Technology Education Specialist Indiana Department of Education Indiana STANDARDS FOR TECHNOLOGICAL LITERACY Mike Fitzgerald Technology Education Specialist Indiana Department of Education Summer 2004 1 Logistics Introductions Workshop Registration/Evaluation Forms

More information

Humanities new methods Challenges for confirmation theory

Humanities new methods Challenges for confirmation theory Datum 15.06.2012 Humanities new methods Challenges for confirmation theory Presentation for The Making of the Humanities III Jan-Willem Romeijn Faculty of Philosophy University of Groningen Interactive

More information

Neighborhood Data and Database Security

Neighborhood Data and Database Security Neighborhood Data and Database Security Kioumars Yazdanian, FrkdCric Cuppens e-mail: yaz@ tls-cs.cert.fr - cuppens@ tls-cs.cert.fr CERT / ONERA, Dept. of Computer Science 2 avenue E. Belin, B.P. 4025,31055

More information

Static Program Transformations for Efficient Software Model Checking

Static Program Transformations for Efficient Software Model Checking Static Program Transformations for Efficient Software Model Checking Shobha Vasudevan Jacob Abraham The University of Texas at Austin Dependable Systems Large and complex systems Software faults are major

More information

1/9. Locke 1: Critique of Innate Ideas

1/9. Locke 1: Critique of Innate Ideas 1/9 Locke 1: Critique of Innate Ideas This week we are going to begin looking at a new area by turning our attention to the work of John Locke, who is probably the most famous English philosopher of all

More information

Semantic Groundedness

Semantic Groundedness Semantic Groundedness Hannes Leitgeb LMU Munich August 2011 Hannes Leitgeb (LMU Munich) Semantic Groundedness August 2011 1 / 20 Luca told you about groundedness in set theory. Now we turn to groundedness

More information

Degrees of Truth: the formal logic of classical and quantum probabilities as well as fuzzy sets.

Degrees of Truth: the formal logic of classical and quantum probabilities as well as fuzzy sets. Degrees of Truth: the formal logic of classical and quantum probabilities as well as fuzzy sets. Logic is the study of reasoning. A language of propositions is fundamental to this study as well as true

More information

Sanford Shieh UNDECIDABILITY, EPISTEMOLOGY AND ANTI-REALIST INTUITIONISM

Sanford Shieh UNDECIDABILITY, EPISTEMOLOGY AND ANTI-REALIST INTUITIONISM Sanford Shieh UNDECIDABILITY, EPISTEMOLOGY AND ANTI-REALIST INTUITIONISM In this paper I show that Michael Dummett s anti-realist intuitionism requires a significant place for epistemic principles. Specifically,

More information

Could I Have Been a Turnip? A Very Short Introduction to the Philosophy of Modality

Could I Have Been a Turnip? A Very Short Introduction to the Philosophy of Modality Could I Have Been a Turnip? A Very Short Introduction to the Philosophy of Modality Modality If something is possible, it could have happened. If something is necessary, it had to happen. If something

More information

A Review of Agent-Oriented Development Methodologies and Programming Languages/Frameworks

A Review of Agent-Oriented Development Methodologies and Programming Languages/Frameworks A Review of Agent-Oriented Development Methodologies and Programming Languages/Frameworks Khalil Salah Advanced Informatics School Universiti Teknologi Malaysia Kuala Lumpur, 54100, Malaysia Ardavan Ashabi

More information

The Language of Social Software

The Language of Social Software The Language of Social Software Jan van Eijck CWI, Amsterdam Workshop on Logic and Social Interaction, Chennai, January 8, 2009 Abstract Computer software is written in languages like C, Java or Haskell.

More information

Information security risk management using ISO/IEC 27005:2008

Information security risk management using ISO/IEC 27005:2008 Information security risk management using ISO/IEC 27005:2008 Hervé Cholez / Sébastien Pineau Centre de Recherche Public Henri Tudor herve.cholez@tudor.lu sebastien.pineau@tudor.lu March, 29 th 2011 1

More information

When is Reputation Bad? 1

When is Reputation Bad? 1 When is Reputation Bad? 1 Jeffrey Ely Drew Fudenberg David K Levine 2 First Version: April 22, 2002 This Version: November 20, 2005 Abstract: In traditional reputation theory, the ability to build a reputation

More information

Quine on truth by convention

Quine on truth by convention Quine on truth by convention March 8, 2005 1 Linguistic explanations of necessity and the a priori.............. 1 2 Relative and absolute truth by definition.................... 2 3 Is logic true by convention?...........................

More information

TECH. Requirements. Why are requirements important? The Requirements Process REQUIREMENTS ELICITATION AND ANALYSIS. Requirements vs.

TECH. Requirements. Why are requirements important? The Requirements Process REQUIREMENTS ELICITATION AND ANALYSIS. Requirements vs. CH04 Capturing the Requirements Understanding what the customers and users expect the system to do * The Requirements Process * Types of Requirements * Characteristics of Requirements * How to Express

More information

Reinforcement Learning of Task Plans for Real Robot Systems

Reinforcement Learning of Task Plans for Real Robot Systems Reinforcement Learning of Task Plans for Real Robot Systems Pedro Tomás Mendes Resende pedro.resende@ist.utl.pt Instituto Superior Técnico, Lisboa, Portugal October 2014 Abstract This paper is the extended

More information

Beyond GDP and new indicators of well-being: is it possible to sum up objective and subjective data in the perspective of constructing new indicators?

Beyond GDP and new indicators of well-being: is it possible to sum up objective and subjective data in the perspective of constructing new indicators? Beyond GDP and new indicators of well-being: is it possible to sum up objective and subjective data in the perspective of constructing new indicators? Filomena Maggino Università degli Studi di Firenze

More information

Hedaquin: A reputation-based health data quality indicator

Hedaquin: A reputation-based health data quality indicator STM 2007 Hedaquin: A reputation-based health data quality indicator Ton van Deursen a,b, Paul Koster a, Milan Petković a a Philips Research Eindhoven, The Netherlands b Université du Luxembourg, Luxembourg

More information

Reliable Personal Health Records

Reliable Personal Health Records Reliable Personal Health Records Ton VAN DEURSEN a,b, Paul KOSTER a and Milan PETKOVIĆ a a Philips Research Eindhoven, The Netherlands b Université du Luxembourg, Luxembourg Abstract. A number of applications

More information

(LMCS, p. 317) V.1. First Order Logic. This is the most powerful, most expressive logic that we will examine.

(LMCS, p. 317) V.1. First Order Logic. This is the most powerful, most expressive logic that we will examine. (LMCS, p. 317) V.1 First Order Logic This is the most powerful, most expressive logic that we will examine. Our version of first-order logic will use the following symbols: variables connectives (,,,,

More information

Rigorous Software Development CSCI-GA 3033-009

Rigorous Software Development CSCI-GA 3033-009 Rigorous Software Development CSCI-GA 3033-009 Instructor: Thomas Wies Spring 2013 Lecture 11 Semantics of Programming Languages Denotational Semantics Meaning of a program is defined as the mathematical

More information

Detecting Deception in Reputation Management

Detecting Deception in Reputation Management Detecting Deception in Reputation Management Bin Yu Department of Computer Science North Carolina State University Raleigh, NC 27695-7535, USA byu@eos.ncsu.edu Munindar P. Singh Department of Computer

More information

Review on computational trust and reputation models

Review on computational trust and reputation models Review on computational trust and reputation models Jordi Sabater and Carles Sierra IIIA - CSIC, Campus UAB, Bellaterra, Barcelona, Spain September 18, 2003 Abstract. The scientific research in the area

More information

Jaakko Hintikka Boston University. and. Ilpo Halonen University of Helsinki INTERPOLATION AS EXPLANATION

Jaakko Hintikka Boston University. and. Ilpo Halonen University of Helsinki INTERPOLATION AS EXPLANATION Jaakko Hintikka Boston University and Ilpo Halonen University of Helsinki INTERPOLATION AS EXPLANATION INTERPOLATION AS EXPLANATION In the study of explanation, one can distinguish two main trends. On

More information

CUNSHENG DING HKUST, Hong Kong. Computer Security. Computer Security. Cunsheng DING, HKUST COMP4631

CUNSHENG DING HKUST, Hong Kong. Computer Security. Computer Security. Cunsheng DING, HKUST COMP4631 Cunsheng DING, HKUST Lecture 08: Key Management for One-key Ciphers Topics of this Lecture 1. The generation and distribution of secret keys. 2. A key distribution protocol with a key distribution center.

More information

Optimizing Description Logic Subsumption

Optimizing Description Logic Subsumption Topics in Knowledge Representation and Reasoning Optimizing Description Logic Subsumption Maryam Fazel-Zarandi Company Department of Computer Science University of Toronto Outline Introduction Optimization

More information

JOINT ATTENTION. Kaplan and Hafner (2006) Florian Niefind Coli, Universität des Saarlandes SS 2010

JOINT ATTENTION. Kaplan and Hafner (2006) Florian Niefind Coli, Universität des Saarlandes SS 2010 JOINT ATTENTION Kaplan and Hafner (2006) Florian Niefind Coli, Universität des Saarlandes SS 2010 1 1 1.Outline 2.Joint attention - an informal approximation 3.Motivation of the paper 4.Formalization of

More information

Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett

Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett Lecture Note 1 Set and Probability Theory MIT 14.30 Spring 2006 Herman Bennett 1 Set Theory 1.1 Definitions and Theorems 1. Experiment: any action or process whose outcome is subject to uncertainty. 2.

More information

UNBOUND ANAPHORIC PRONOUNS: E-TYPE, DYNAMIC, AND STRUCTURED-PROPOSITIONS APPROACHES

UNBOUND ANAPHORIC PRONOUNS: E-TYPE, DYNAMIC, AND STRUCTURED-PROPOSITIONS APPROACHES FRIEDERIKE MOLTMANN UNBOUND ANAPHORIC PRONOUNS: E-TYPE, DYNAMIC, AND STRUCTURED-PROPOSITIONS APPROACHES ABSTRACT. Unbound anaphoric pronouns or E-type pronouns have presented notorious problems for semantic

More information

Dedekind s forgotten axiom and why we should teach it (and why we shouldn t teach mathematical induction in our calculus classes)

Dedekind s forgotten axiom and why we should teach it (and why we shouldn t teach mathematical induction in our calculus classes) Dedekind s forgotten axiom and why we should teach it (and why we shouldn t teach mathematical induction in our calculus classes) by Jim Propp (UMass Lowell) March 14, 2010 1 / 29 Completeness Three common

More information

Correspondence analysis for strong three-valued logic

Correspondence analysis for strong three-valued logic Correspondence analysis for strong three-valued logic A. Tamminga abstract. I apply Kooi and Tamminga s (2012) idea of correspondence analysis for many-valued logics to strong three-valued logic (K 3 ).

More information

Customer Experience Management architecture for enhancing corporate customer centric capabilities

Customer Experience Management architecture for enhancing corporate customer centric capabilities Customer Experience Management architecture for enhancing corporate customer centric capabilities Dominik Ryżko 1 and Jan Kaczmarek 1 Warsaw University of Technology, Intitute of Computer Science, Ul.

More information

Verification of multiagent systems via ordered binary decision diagrams: an algorithm and its implementation

Verification of multiagent systems via ordered binary decision diagrams: an algorithm and its implementation Verification of multiagent systems via ordered binary decision diagrams: an algorithm and its implementation Franco Raimondi Alessio Lomuscio Department of Computer Science King s College London London

More information

Business Definitions for Data Management Professionals

Business Definitions for Data Management Professionals Realising the value of your information TM Powered by Intraversed Business Definitions for Data Management Professionals Intralign User Guide Excerpt Copyright Intraversed Pty Ltd, 2010, 2014 W-DE-2015-0004

More information